The Era Of SaaS 2.0: How AI And ML Are Bringing Change

As the software-as-a-service, or SaaS, model has risen in popularity in recent years and is becoming an increasingly viable choice for companies searching for functionality, accessibility, and versatility, it continues to offer cutting-edge solutions in a broad array of industries. And as the competition among SaaS products continues to rise, so do customer expectations and their needs to solve particular issues within their organizations. 

Any successful SaaS integration permits organizations to run SaaS software solutions without the need to depend on installing and running applications on their own data centers and computer systems. As such, these technological novelties rise in popularity every year, and we find ourselves in the early stages of large-scale SaaS integration within consumers. 

SaaS 2.0 is taking over the cloud computing market for good. Technavio’s “SaaS Market by Deployment and Geography - Forecast and Analysis 2021-2025” report indicates that SaaS products will significantly impact the post-Covid-19 market and help organizations better evaluate their business processes. Moreover, the same report forecasts that the global SaaS industry is anticipated to be worth $60.3 billion by 2023, an increase of almost 10% in the next two years, with 37% of SaaS companies suggesting flexibility as the most significant component for adopting cloud-based systems.

Photo from Salesforce

The last couple of years were really breakthrough years for the SaaS world in many ways. Still, with SaaS 2.0 on the horizon, in this blog post, we’ll explore the most significant trends that will stand out in the years to come and cause a wave of disruptive change in the industry. At the moment, artificial intelligence and its subcategories - machine learning and natural language processing - are the ones that are bringing this disruptive change at a rapid pace. For that reason, we are firm believers in the thesis that companies that will ride on the SaaS artificial intelligence wave will be the ones that will outperform competitors in the future. So, without further ado, here’s how AI and NLP are doing it already!

The Emergence Of SaaS 2.0 

In a nutshell, SaaS is a software distribution model in which a third-party provider has applications and makes them available to customers over cloud computing and the Internet. SaaS models discharge the requirements for companies to install and run applications all alone on systems in their own data centers and eliminate the hefty costs of hardware acquisition, provisioning, maintenance, software permitting, installation, and backing.

Photo from Entrepreneur  

SaaS 2.0 is the subsequent evolutionary stage of the conventional SaaS models, concentrating more on conveying a service provisioning platform towards integrated businesses. This model is envisioned to radically change the understanding of SaaS from only a disseminated software carrying platform to a model that gives a management platform integrated sophisticated service-oriented architecture and business process management. In 2021, most of the SaaS 2.0 based solutions are accompanied by the following attributes: 

  • Modern-day SaaS solutions provide more adaptable, secure, and practical business and work processes within organizations. Nowadays, the essential business driver for SaaS solutions is assisting clients in transforming their business processes and structures. At the same time, the ultimate goal of such solutions is to permit organizations to reach business targets in a much shorter period. 
  • SaaS service providers and vendors differentiate themselves by providing a broad range of value-add business modules that offer companies a blend of business process, application functionality, and managed services at an operational level.
  • SaaS 2.0 is characterized by its cascading and radiating impact of business improvement and internal change within organizations across and past the user enterprise. Essentially, a SaaS integration can enhance business decisions, efficiencies, and business capabilities inside the client undertaking, between the company and its clients, suppliers, and business partners.

Now that we’ve explained the key characteristics of SaaS innovations, it’s time to take a deep dive into how artificial intelligence and its subdivisions natural language processing and machine learning bring disruptive changes to the industry and shape the sector for the foreseeable future.

The New Era Is Here, And Artificial Intelligence Is Leading The Charge 

Nowadays, AI is deep-rooted in the veins of our society, and it’s becoming a real game-changer for companies, with an estimated market value of $733 billion by 2027. Artificial intelligence is perhaps the most innovative technology that brings disruptive change to the entire SaaS model. AI-based SaaS integration brings many benefits to the table for modern-day organizations. The most notable is hyper-personalization, which allows satisfying customer needs in B2B, B2C, and DTC markets. 

Photo from IEEE Innovation At Work

Besides, it optimizes business processes, increases productivity and efficiency, and automates repetitive tasks, supporting human capabilities, especially in the customer service automation efforts. Within business scenarios, artificial intelligence, when combined with natural language processing and machine learning, offers an advanced degree of responsiveness and interaction between customers, businesses, and technology, driving AI-based SaaS solutions to a whole new level.

Other than customer service, there are many other AI-based SaaS features developed by software providers, such as data alerts. With an AI algorithm using the most sophisticated neural network for anomaly detection, and a machine learning algorithm for pattern recognition, these data alerts learn from patterns and trends and let companies know as soon as something significant happens in their daily scope of work. Thus, when a pre-set goal is met or something unexpected happens, the company data scientists get notified, enabling executives to control their business continuously.

In a few words, artificial intelligence and its subcategories are positioned to disrupt the SaaS 2.0 landscape in a few different ways, improving the crucial characteristics of the SaaS integration model across the board. When SaaS 2.0 is combined with artificial intelligence capabilities, it permits companies to get better value from their data, automate and personalize services, enhance security, and supplement human capacity like no other technology.  

Bottom line, AI assists in building a shiny SaaS future thanks to its three cornerstone traits: personalization, speed, and security: 

  • Personalization. AI-powered SaaS solutions are easier to use with NLP, which automatically processes voice control and human speech patterns. Y Meadows software can be deployed for better customer service functionality, improve customization, and better address client needs. 
  • Speed. AI-enabled SaaS speeds up internal business operations and processes, permitting organizations to obtain fast answers to questions, make prompt forecasts, and speed up their level of responsiveness. 
  • Security. Because of artificial intelligence-powered automation and the ability of machine learning to recognize patterns, SaaS security is increased by the swift identification and remedy of potential threats with built-in self-recovery.
Photo from Medium

Machine Learning 

Machine learning, which practically is a subset of artificial intelligence, is utilized in SaaS to automate responsiveness in customer service reports and applications, like AI-enabled chat operations through various forms of virtual assistants. Machine learning also automates the onboarding process of SaaS, as machine learning is built on autonomous operational models so that innovations will facilitate platforms and software to automate significant chunks of internal processes other than customer service and experience alone. 

Photo from SAP

ML is one of the fastest-growing partitions of software, and, as such, it will remain a hot SaaS topic for the time to come. Moreover, as machine learning is an integral part of artificial intelligence-based SaaS models, it only fits to assume that an increasing number of platforms will emerge to help companies across the following sectors:

  • Train their existing software to learn from each interaction or task, gaining a greater level of intelligence and efficiency in the process. 
  • Dig a little deeper into contextual data and insights to gain a noticeable edge on the competition. 
  • Enhance internal collaboration and operations via more advanced communication models.

The AI-Centered Era Of SaaS Is Here To Stay 

In conclusion, artificial intelligence represents the onset of the new era for consumers and businesses—one that allows organizations to be more efficient in high-volume manual operations and attentive to their clients. AI technologies are also inspiring disruptive SaaS products by scaling human-like knowledge to solve previously unscalable bottleneck problems. So, in an industry that adapts and evolves at incredible speed, businesses that want to crash shores before competitors must save a seat for artificial intelligence and machine learning in their tech stack.

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